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The individual experience of inadequate or insufficient sleep is one of the most common health issues in the industrialized world. The 65% of Italian population reports disturbed sleep experiences, while chronic sleep disorders affect about 10% of the population. The people with inadequate and uns…

The individual experience of inadequate or insufficient sleep is one of the most common health issues in the industrialized world. The 65% of Italian population reports disturbed sleep experiences, while chronic sleep disorders affect about 10% of the population. The people with inadequate and unsatisfactory sleep often suffers drowsiness during the day associated with both somatic and mental disorders. For these reasons, the systematic and continuative monitoring of sleep is one of the main objectives in preventive, personalized and participatory sleep medicine. The purpose of this paper is to describe the architecture of a “smart mattress’’ (SmartBed) that is the main outcome of the Italian R&D project called LAID. SmartBed will be able to non-obtrusively collect physiological and environmental parameters and signals, to processing them and to provide information about the quality of sleep, the levels of stress, and more generally the well-being of an individual. Specifically, SmartBed will be able to estimate data relating to cardiorespiratory activity, movements, body position, snoring and environmental parameters. SmartBed aims to obtain a continuative and ecological assessment of sleep and well-being of a person, in order to improve his quality of life. SmartBed will be a fundamental tool for carrying out both longitudinal and epidemiological studies on the quality of sleep and life on general population.

Anxiety-related disorders have a strong impact on our quality of life. With their epidemiological prevalence, across the population, highly exceeding the capacity for treatment in health facilities, new ways of delivering therapies are needed. The wide availability of mobile technologies, e.g., sma…

Anxiety-related disorders have a strong impact on our quality of life. With their epidemiological prevalence, across the population, highly exceeding the capacity for treatment in health facilities, new ways of delivering therapies are needed. The wide availability of mobile technologies, e.g., smartphones, has provided an accessible and ubiquitous platform for delivering psychological therapies and many mobile health (mHealth) systems have been proposed to support users in managing their levels of anxiety. However, many of the available tools provide features without evidence-based support of their adequateness and effectiveness. Furthermore, several tools are designed without specifically considering the users’ needs and motivations, resulting in poor adherence or a lack of motivation for systematic use, hindering any positive effects.

The concept of an Integrated Clinical Environment can be implemented by a fully connected operation room containing devices from different manufacturers. An exchange architecture and protocol for this kind of environment is defined by the IEEE 11073 Service-oriented Device Connectivity family of st…

The concept of an Integrated Clinical Environment can be implemented by a fully connected operation room containing devices from different manufacturers. An exchange architecture and protocol for this kind of environment is defined by the IEEE 11073 Service-oriented Device Connectivity family of standards. Therein, a Domain Information and Service Model is bound to the Medical Devices Communication Profile for Web Services, which is the specification for the information exchange technology. It is employed as the communication layer in the software library SDCLib/J that implements an Integrated Clinical Environment. In order to demonstrate that the functionality of SDCLib/J is independent of the underlying transport technology, its communication layer was replaced with an implementation of the Data Distribution Service. Therefore, its publish-subscribe pattern needed to be redesigned and transformed so that it matches the library’s request-response principle.

Objective: Timely and effective discrimination of hemorrhagic stroke and ischemic stroke can significantly improve the prognosis. Current discrimination is expensive and has the disadvantage of having to be in contact with the patient. Based on animal experiments, in this paper, microwave measurem…

Objective: Timely and effective discrimination of hemorrhagic stroke and ischemic stroke can significantly improve the prognosis. Current discrimination is expensive and has the disadvantage of having to be in contact with the patient. Based on animal experiments, in this paper, microwave measurement technique is used to study the discrimination of two stroke types. Method: In the experiments, 10 rabbits (5 cerebral hemorrhage and 5 cerebral ischemia) are selected. Cerebral hemorrhage is induced by injecting autologous blood (1 to 4 mL) into the brain of rabbits, and the cerebral ischemia is induced by bilateral common carotid artery ligation and femoral artery blood extraction. The two groups are monitored by a 16-channel microwave detection system to obtain the reflection parameter caused by pathological changes in the brain. After redundancy removed from original data, support vector machine (SVM) is used to identify the type and severity of two types of stroke. Findings: The study shows that the microwave-based stroke identification system can effectively distinguish the cerebral hemorrhage model and the cerebral ischemia model. The experimental system is very promising in pre-hospital stroke type identification because of low cost, non-invasive, simple operation and rapid measurement.

Nowadays, wearable devices enable us to collect biological data from a massive number of people. However, the reliability of the collected data varies due to various factors such as band tightness and incorrect attachment. In this paper, we investigate the band tightness estimation by using an ine…

Nowadays, wearable devices enable us to collect biological data from a massive number of people. However, the reliability of the collected data varies due to various factors such as band tightness and incorrect attachment. In this paper, we investigate the band tightness estimation by using an inertial sensor of a wrist-worn device. First, we analyze the relationship between the band tightness and the data reliability through a preliminary experiment. Then, we design the band tightness estimation as a classification problem based on frequency domain features. The evaluation results show the effectiveness of the frequency domain features, achieving the accuracy of 81.7% for the 3-class band tightness classification.

Current wellness technologies are capable of monitoring wellness related parameters even 24 h a day for multiple days. The aim of the current research was to study the usability, user experience, and wellbeing impact of the wellness analysis Firstbeat, which is based on continuous measurement of he…

Current wellness technologies are capable of monitoring wellness related parameters even 24 h a day for multiple days. The aim of the current research was to study the usability, user experience, and wellbeing impact of the wellness analysis Firstbeat, which is based on continuous measurement of heart rate variability (HRV) and user activity. 42 persons in working life participated in an intervention study, in which their wellbeing was continuously monitored for 3–7 days and they received a detailed wellness report and a personal plan for improvement. In a follow-up questionnaire, the participants reported good usability and user experience for the system, as well as significantly reduced stress and increased self-esteem, while no significant changes were observed in the other measured aspects related to subjective wellbeing. The results suggest that the usage of continuous wellness measurement systems using electrodes in the chest area, such as Firstbeat, can be experienced positively by their users. Further research is needed on effective methods for utilizing the rich information from the measurements in achieving lasting positive changes in lifestyle.

The paradigm of citizen-science, i.e., scientific research that is conducted in whole or in part by non-professional scientists, has gained popularity lately, e.g., for the purpose of crowdsourced data collection. Smartphones with their abundance and ubiquity are perfectly suited and have been wide…

The paradigm of citizen-science, i.e., scientific research that is conducted in whole or in part by non-professional scientists, has gained popularity lately, e.g., for the purpose of crowdsourced data collection. Smartphones with their abundance and ubiquity are perfectly suited and have been widely used for crowdsourced data collection in real life settings. The ongoing, EC-funded research programme named BigO exploits the citizen-science paradigm to collect behavioral (eating, sleeping and physical activity) and affective (mood) data from children populations by means of a novel smartphone application with the intention of developing a decision support system to assist public health authorities in effective policy making against childhood obesity. This paper presents the development – in the context of BigO – of the myBigO app, one of the first citizen-scientist smartphone applications addressed to children for behavioral and affective data collection. This includes the design, implementation, and deployment of myBigO app in a number of data collection studies as well as its preliminary evaluation with respect to technical robustness and user experience in the context of these studies.

Traditional cloud-centric architectures for Internet-of-Things applications are being replaced by distributed approaches. The Edge and Fog computing paradigms crystallize the concept of moving computation towards the edge of the network, closer to where the data originates. This has important benef…

Traditional cloud-centric architectures for Internet-of-Things applications are being replaced by distributed approaches. The Edge and Fog computing paradigms crystallize the concept of moving computation towards the edge of the network, closer to where the data originates. This has important benefits in terms of energy efficiency, network load optimization and latency control. The combination of these paradigms with embedded artificial intelligence in edge devices, or Edge AI, enables further improvements. In turn, the development of blockchain technology and distributed architectures for peer-to-peer communication and trade allows for higher levels of security. This can have a significant impact on data-sensitive and mission-critical applications in the IoT. In this paper, we discuss the potential of an Edge AI capable system architecture for the Blockchain of Things. We show how this architecture can be utilized in health monitoring applications. Furthermore, by analyzing raw data directly at the edge layer, we inherently avoid the possibility of breaches of sensitive information, as raw data is never stored nor transferred outside of the local network.

This paper presents a novel two-fingers exoskeleton kinesthetic interaction in Virtual Reality (VR): the proposed design of the exoskeleton prioritizes the performance of the device in terms of low weight, good adaptability to different size of the human hand. This design made also the exoskeleton …

This paper presents a novel two-fingers exoskeleton kinesthetic interaction in Virtual Reality (VR): the proposed design of the exoskeleton prioritizes the performance of the device in terms of low weight, good adaptability to different size of the human hand. This design made also the exoskeleton well wearable and allows strong force feedback which is an important parameter for a realistic kinesthesis of manipulated objects in VR.

Walking has been attracting attention as an important means for prevention and improvement of lifestyle diseases, such as high blood pressure and diabetes. However, walking at a continuous pace with high load can be challenging, and health benefits cannot be expected when walking with low load. …

Walking has been attracting attention as an important means for prevention and improvement of lifestyle diseases, such as high blood pressure and diabetes. However, walking at a continuous pace with high load can be challenging, and health benefits cannot be expected when walking with low load. A walking pace support system is necessary in order to achieve effective walking. Hence, we are developing BeatSync, a smartphone application that realizes the induction of a natural and accurate walking pace by the rhythm of music. This application can select songs from a user’s music library. However, some songs, such as songs with a fast (slow) rhythm or complex beats, are not suitable for walking pace induction. In the present paper, we consider the speed and clarity of music rhythm to be an important factor in selecting a song that is suitable for walking pace induction and make an index and clarify its effect on walking pace induction. In the present study, BPM is used as an index of rhythm speed, and RhythmValue (RV) is proposed as an index of rhythm clarity. In order to verify the effectiveness of the index, we conducted walking pace induction experiments using 30 songs with different speeds and clarities (two sets of 15 songs) with 14 participants. As a result, the experiments confirmed that the proposed index can distinguish songs that are suitable or unsuitable for walking pace induction and can select songs that are suitable for walking pace induction.